Pregnancy-Related Mortality Due to Infection: Maternal Mortality Review Committees in 29 U.S. States, 2017-2019.

OBJECTIVE

To describe demographic and clinical characteristics, preventability, Maternal Mortality Review Committee (MMRC)-determined contributing factors, and example recommendations for pregnancy-related deaths due to infection using data from MMRCs.

METHODS

We used pregnancy-related death data from MMRCs in 29 states occurring during 2017-2019 with MMRC-determined underlying cause of death of infection. We describe the distribution of demographic and clinical characteristics, present the most frequent contributing factor classes, and provide example MMRC prevention recommendations.

RESULTS

Ninety-one pregnancy-related infection deaths were identified, and MMRCs determined that 86.4% of deaths were preventable among 88 deaths for which MMRCs determined preventability. Most deaths occurred within 42 days of delivery (69.3%). Additional clinical information was available for many deaths. Group A streptococci were the most frequently identified pathogen (34.0%, 18/53) and genital tract was the most frequently identified source (47.9%, 35/73) of the infection. The most frequent health care encounter before death was hospitalization (50.7%, 36/71). More than half of decedents (69.1%, 47/68) had a health care encounter less than 7 days before death. The five most frequent contributing factor classes were clinical skill/quality of care (18.6%), delay (10.1%), knowledge (10.1%), lack of continuity of care (9.6%), and lack of access/financial resources (7.8%). The MMRC prevention recommendations occur at multiple levels, addressing frequent contributing factor classes.

CONCLUSION

Most pregnancy-related deaths due to infection are preventable. Example MMRC recommendations highlight prevention opportunities, including improving patient and clinician knowledge regarding clinical signs and symptoms of serious infections, implementing obstetric sepsis protocols, and enhancing care coordination within and across systems.